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Analysis of Term Structures in High Frequencies
Nedvěd, Adam ; Baruník, Jozef (advisor) ; Červinka, Michal (referee)
This thesis represents an in-depth empirical study of the dependence structures within the term structure of interest rates. Firstly, a comprehensive overview of term structure modelling literature and methods is provided together with a summary of theoretical notions regarding the use of high-frequency data and spectral analysis. Contrary to most studies, the frequency-domain approach is employed, with a special focus on dependency across various quantiles of the joint distribution of the term structure. The main results are obtained using the quantile cross-spectral analysis, a new robust and non-parametric method allowing to uncover dependence structures in quantiles of the joint distribution of multivariate time series. The results are estimated using a dataset consisting of 15 years worth of high-frequency tick-by-tick time series of US Treasury futures. Complex dependence structures are revealed showing signs of both cyclicity and dependence in various parts of the joint distribution of the term structure in the frequency domain. JEL Classification C49, C55, C58, E43, G12, G13 Keywords term structure of interest rates, yield curves, high-frequency analysis, spectral analysis, inter- est rate futures Author's e-mail adam.nedved@fsv.cuni.cz Supervisor's e-mail barunik@fsv.cuni.cz
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Analysis of Term Structures in High Frequencies
Nedvěd, Adam ; Baruník, Jozef (advisor) ; Červinka, Michal (referee)
This thesis represents an in-depth empirical study of the dependence structures within the term structure of interest rates. Firstly, a comprehensive overview of term structure modelling literature and methods is provided together with a summary of theoretical notions regarding the use of high-frequency data and spectral analysis. Contrary to most studies, the frequency-domain approach is employed, with a special focus on dependency across various quantiles of the joint distribution of the term structure. The main results are obtained using the quantile cross-spectral analysis, a new robust and non-parametric method allowing to uncover dependence structures in quantiles of the joint distribution of multivariate time series. The results are estimated using a dataset consisting of 15 years worth of high-frequency tick-by-tick time series of US Treasury futures. Complex dependence structures are revealed showing signs of both cyclicity and dependence in various parts of the joint distribution of the term structure in the frequency domain. JEL Classification C49, C55, C58, E43, G12, G13 Keywords term structure of interest rates, yield curves, high-frequency analysis, spectral analysis, inter- est rate futures Author's e-mail adam.nedved@fsv.cuni.cz Supervisor's e-mail barunik@fsv.cuni.cz
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Connectedness of high-frequency data
Petras, Petr ; Křehlík, Tomáš (advisor) ; Maršál, Aleš (referee)
This work combines discrete and continuous methods while modeling connect- edness of financial tick data. As discrete method we are using vector autore- gression. For continuous domain Hawkes process is used, which is special case of point process. We found out that financial assets are connected in non- symmetrical fashion. By using two methodologies we were able to model bet- ter how are the series connected. We confirmed existence of price leader in our three stock portfolio and modeled connectedness of jumps between stocks. As conclusion we state that both methods yields important results about price nature on the market and should be used together or at least with awareness of second approach. JEL Classification C32, G11, G14 Keywords Vector Autoregression, Hawkes process, High- frequency analysis, Connectedness Author's e-mail petr.petras@email.cz Supervisor's e-mail krehlik@utia.cas.cz
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